- New Features
  - Support Java Client
  - Support TensorRT, add docker image for cuda10.1 and TensorRT 6
  - Modify the LocalPredictor interface to align with the RPC interface usage
  - Add Pipeline Serv·ing Dag Deployment
  - Support Windows 10 (Only Web Service and Local Predictor)
  - Add built-in Serving model converter
- Improve of Compatibility
  - Release cuda10.1 version of paddle_serving_server_gpu
  - Release Python 3.5 version of paddle_serving_client
  - Remove serving-client-app circular dependencies
  - Modify version of dependencies
- Improve of Framework
  - Pipeline Dag support multi-gpu
  - lower RPC thread restriction to 1
- Documents
  - Modify "COMPILE"
  - Add "WINDOWS_TUTORIAL"
  - Add "PIPELINE_SERVING"
  - Modify "BERT_10_MIN"
- New Demo
  - pipeline demos
  - Java Demo
- Bug fixes
  - Fix subprocess CUDA ERROR3 bug
  - Fix pip install dependencies
  - Fix import error in windows
  - Fix bugs in web service
  • New Features
    • Support Java Client
    • Support TensorRT, add docker image for cuda10.1 and TensorRT 6
    • Modify the LocalPredictor interface to align with the RPC interface usage
    • Add Pipeline Serving Dag Deployment
    • Support Windows 10 (Only Web Service and Local Predictor)
    • Add built-in Serving model converter
  • Improve of Compatibility
    • Release cuda10.1 version of paddle_serving_server_gpu
    • Release Python 3.5 version of paddle_serving_client
    • Remove serving-client-app circular dependencies
    • Modify version of dependencies
    • Support LoD Tensor and replace list type for batch input with one numpy array
  • Improve of Framework
    • Pipeline Dag support multi-gpu
    • lower RPC thread restriction to 1
  • Documents
    • Modify "COMPILE"
    • Add "WINDOWS_TUTORIAL"
    • Add "PIPELINE_SERVING"
    • Modify "BERT_10_MIN"
  • New Demo
    • pipeline demos
    • Java Demo
  • Bug fixes
    • Fix subprocess CUDA ERROR3 bug
    • Fix pip install dependencies
    • Fix import error in windows
    • Fix bugs in web service

项目简介

A flexible, high-performance carrier for machine learning models(『飞桨』服务化部署框架)

🚀 Github 镜像仓库 🚀

源项目地址

https://github.com/PaddlePaddle/Serving

发行版本 14

Release v0.9.0

全部发行版

贡献者 36

全部贡献者

开发语言

  • C++ 51.6 %
  • Python 27.0 %
  • Shell 8.0 %
  • CMake 6.0 %
  • Go 4.4 %